Artificial Intelligence is a branch of computer science involved in creating computers or machines with a cognitive ability like humans. The evolution of computers has to lead the creation of more and more intelligent machines and programs. Speech recognition, learning, planning and problem solving are the common activities embodied in a computer with artificial intelligence. AI is used extensively in all fields of science and education and is a beacon to the next generation of computing and technology.

Artificial Intelligence involves incorporating features into machines that mimic human intelligence and cognitive attributes like self-learning, visual perception, speech recognition, logical problem solving, and decision making. The Artificial Intelligence field aims to solve human intelligence and put its features in software, robots, and machines in general for increased efficiency in performing tasks that exceed common mathematical boundaries and human capacities. It involves problem-solving skills and pattern recognition from abstract audio-visual or input data, deep learning for automatic error perfection that is ‘self-learning’, prediction capabilities based on present datasets, and accurate simulation from raw data to name a few.

Artificial Intelligence can be adopted into various disciplines such as Computer Science, Biology, Engineering, Mathematics, Neuroscience and Psychology.

Applications of Artificial Intelligence have been dominating in various fields such as:

Gaming: Artificial Intelligence plays a major role in simulating a human-like behavior in the games depicting Non-player characteristics like Tony La Russa Baseball, Madden Football, Earl Weaver Baseball and many other video games.

Natural Language Processing: It is concerned with the interactions between human and computers by understanding the natural language spoken by a person through artificial intelligence technology.

Visual input systems: These systems have the ability to understand, interpret and comprehend from the visual inputs given to the computer. Best example would be Spy or surveillance aircrafts used by military camps to take photographs of airfields, factories and shipyards, and map of the areas where enemies can reach.

Robotic Process Automation: With the advent of automation technologies, industries are able to control, interpret, and manage their back-end and middle office tasks with the help of robots in a smooth manner by self-learning and self-correcting, simultaneously reducing costs.

Biometrics: Biometric systems are used to recognize and identify the people by analyzing the behavioral statistics (which can be speech, body language, fingerprints etc.,) through computerized methods. Biometric Systems are used in passports, laptops or mobile security, office attendance systems and many other areas.

Machine learning platforms: These platforms are used as a service for finding patterns, predictive analytics, classifying and understanding big data. It can also be applied to neural networks, face recognition, voice recognition and Natural Language Processing (NLP). Google, Amazon, and IBM are offering free accounts in the form of APIs for the developers to understand and create models, regardless of any knowledge of Machine Learning (ML) algorithms.

Virtual agents: Virtual agents exhibit animated human-like characteristics, representing as a customer service provider for the online customers. Many companies running online businesses use chatbots in their websites for interacting with their customers, where the conversations are already custom defined.

AI in Computational Biology

By developing machine learning algorithms, it is possible to retrieve biological information of an individual from their DNA, gene expression levels and various tissues used to predict or diagnose disease or develop the best therapy for that particular individual. But the challenge is to understand the genetic and molecular mechanisms that cause diseases, and this can be solved by modernistic machine learning techniquesin the future.

Artificial Intelligence in HR Analytics

AI in HR can be a good target as many HR practices are manually generated and could be even better. According to a research by Bersin’s firm, nearly 40 percent of companies are using different forms of Artificial Intelligence in HR. AI applications in HR can help to decide which applicant best fits based on the attributes and their background. To conduct a most productive interview, these AI software applications perform in-depth analysis on data available fromsocial media networks and online surveys to spot successful employees.

AI in Banking

Artificial Intelligence is no longer a new apparatus forBanking and Financial industries, as they are already finding success in implementing AI. The benefit of AI in banks and credit unions is prevailing, reaching back office operations, compliance, customer experience, risk management and marketing to name a few. But still, most of the banks and credit unions are still in the early stage of using AI technologies, says a report surveyed by Narrative Science. The survey even confirmed that 32 percent of financial services are using AI technologies like predictive analytics, recommendation engines, voice recognition and response.

AI in Retail

AI is a game changer, occupying almost all the industries and by no means, retail is a special case. AI can contribute to let the retail industry evolve into something new and unexpected fame.

Store Footprint Optimization—Opening a new store has always been a tough choice to be made for the retailers. Through the Artificial Intelligence technologies or smart algorithms, retailers can take into account the historical sales data, demographics, nearby events and weather patterns to decide whether or not to open a new store.

Virtual Mirrors—Indecisiveness inside a store, especially while shopping clothing and accessories is a common problem for any customer. “What suits me best?” is a routine question which keeps bothering every customer before purchasing. A virtual mirror is a new AI technology that helps customers to try various options ranging from sizes, colors, and items before the checkout process. And, the retailers adopting virtual mirrors technology in their in-store activities can experience great customer satisfaction and improve their identity in the market.

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